Markets as connected systems
Research
My work combines asset pricing, macro-finance, international networks, and artificial intelligence to study how expectations, technology, and intelligent systems propagate through economies.
Asset Pricing
How beliefs, risk, and market structure become encoded in prices and expected returns.
MacroFinance
How international imbalances, intermediaries, and financial frictions shape currencies and capital flows.
AI in Finance
How intelligent systems reshape production, firms, markets, human capital, and the allocation of economic activity.
Quantitative Finance
Computational and statistical tools for high-dimensional, networked, and data-rich financial problems.
Working paper
International beliefs network and currencies
We construct a multicountry model in which bilateral trade imbalances must be financed through international intermediaries subject to trading frictions. Multiple intermediaries can finance the same country-pair imbalance and may hold different beliefs about each country's future external debt capacity.
By no arbitrage, currency adjustments are determined by the full network of intermediary expectations, with greater weight assigned to intermediaries with higher local centrality. The project tests new empirical predictions linking exchange rates and current-account imbalances to Consensus Economics survey data for G-10 currencies and China from 1990 to 2023.
Research area
AI in Finance
My research in this area asks how intelligent systems alter the economy more broadly: production, firm organization, market structure, decision-making, human-capital formation, and the distribution of economic activity.
Current project
Artificial intelligence and the transformation of skilled work
We develop a macroeconomic model of how AI changes the allocation and accumulation of skilled labor across junior and senior roles. The project studies implications for production, human capital, career progression, and policies that account for the social value of training, data creation, and workforce development.
Published research
A Flexible Approach to Interference Cancellation in Distributed Sensor Networks
This work develops a performance-aware weighting method for distributed networks in which noisy or malfunctioning nodes can mislead their neighbors. Applied to diffusion LMS algorithms, the method adapts combination weights to recent node behavior and remains robust when network conditions change.
Research contributions
Academic service and supporting work
- Academic RefereeEconomics Letters (Elsevier)
- Solutions ManualHigh-Dimensional Statistics: A Non-Asymptotic Viewpoint by Martin J. Wainwright (unpublished)